FREE Adversarial AI Course out now on plebdevs.com 🤝👩💻🤝🧑💻🤝👨💻🤝
Lesson 6 in the PlebDevs Adversarial AI Course: We can now put all of our learnings to the test by going through the adversarial build where we will build a full working project end-to-end with only local and private AI tools following the plebdevs new-project-boilerplate template and runbook.
This lesson shows you how to kick off a new project with clear documentation, better planning, and a workflow that works well with AI tools.
Learn to run your goose agent with local AI models powered by ollama
Learn to run your opencode coding agent with local AI models powered by ollama
Learn about how to choose your software techstack and approach a new project from zero when building with AI leveraging the PlebDevs "AI Guides" and "Freedom Tech" repos
SearXNG is a self-hosted metasearch engine that lets you run private web search on your own machine. For local AI workflows, it pairs especially well with coding agents and local model hosts because it exposes a simple JSON search API.
Lesson 3 shifts from AI concepts into AI interfaces and local agents: what an AI agent actually is, how to choose the right interface for the job, and how tools, providers, memory, and privacy all change depending on where and how you use AI. We’ll compare UI, IDE, CLI, API, task-runner, and automation workflows, then walk through practical local-first options so you can use AI more powerfully without blindly handing your data to the cloud.
Lesson 2 continues our intro to AI from the backend this time with a focus on AI model providers: - What is an AI provider? - What are their business models and incentives? - How to evaluate and vet providers? - How to be your own provider? These questions and many more will be explored in lesson 2!
This is a single consolidated guide for running local models with Ollama and connecting tools and agents (especially Goose) to your local Ollama server. It merges the core Desktop, CLI, and Goose workflows into one practical "happy path + operations" reference.
Lesson 1 is a practical intro to AI from the backend: what an AI model is, how to evaluate models (params, open vs closed, context window, speed/cost), and how to run LLMs locally—starting with Ollama
High level intro and overview and framing for the course
Lesson 8 in the PlebDevs Adversarial AI Course - COMING SOON
Lesson 7 in the PlebDevs Adversarial AI Course - COMING SOON
In this lesson, we'll bring our web pages to life by adding dynamic functionality with JavaScript. We'll build a real-world application that displays and updates Bitcoin prices in real-time, teaching core JavaScript concepts along the way.
In the previous lesson, we created the structure of our webpage with HTML. Now, we'll learn how to style it using CSS (Cascading Style Sheets). While HTML provides the bones of our webpage, CSS adds the visual presentation - the colors, layouts, spacing, and overall aesthetics.
PlebDevs Course II: Building a Lightning Wallet Backend
Now that everything is built, tested, and working, we can deploy our server, database, Lightning Node, and frontend App to production!
Integrate the Lightning Wallet backend we've been building into the pleb-wallet Frontend App
Learn to interact with your database through the API of your server
Learn how to setup a local database on your server end-to-end using the Knex library
